Javad Taherpoor; Ali Arab Mazar Yazdi; Mahshid Malekhosseini
Abstract
Financial instability poses a challenge for developing countries, particularly oil-dependent developing nations, due to their reliance on windfall oil revenues. During periods of abundant oil income, governments tend to increase spending under political pressures, while during times of declining ...
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Financial instability poses a challenge for developing countries, particularly oil-dependent developing nations, due to their reliance on windfall oil revenues. During periods of abundant oil income, governments tend to increase spending under political pressures, while during times of declining revenues, they struggle to reduce expenditures proportionally due to spending rigidities. In this context, institutional quality appears to influence fiscal sustainability by fostering fiscal discipline. Accordingly, this study examined the impact of institutional quality on fiscal sustainability in 11 oil-producing developing countries and 16 non-oil developing countries from 2010 to 2020, using panel regression models and the PCSE technique. To measure institutional quality, three indicators were used: control of corruption, rule of law, and regulatory quality, while fiscal sustainability was measured by budget deficit volatility. The estimation results indicate a negative relationship between budget deficit volatility and institutional quality indicators. Furthermore, a comparative analysis revealed that the effects of corruption control and regulatory quality are stronger in oil-producing developing countries, whereas the rule of law has a greater impact on budget deficit volatility in non-oil developing countries.
Introduction
The mismatch between the growth of government revenues and expenditures has turned fiscal instability into a serious challenge in developing countries, particularly in many oil-dependent developing nations. In these countries, governments control windfall oil revenues and, disregarding their finite and volatile nature, expand their expenditures—especially consumptive spending—to gain political support, thereby exacerbating fiscal instability. Iran, too, has faced fiscal instability due to its long-term reliance on windfall oil revenues, which the government has used to expand consumptive expenditures (through hiring, wage payments, subsidies, etc.), as well as to finance the legacy of the eight-year Iran-Iraq war. Therefore, this research aims to examine how institutional quality affects the fiscal sustainability of governments and how this effect differs between oil-rich and non-oil developing countries.
Method
The present study estimates the aforementioned model once for oil-rich developing countries and once for non-oil developing countries using panel data models and the PCSE technique, with Stata 17. After estimating the models, the results of the two models were compared using a Z-test.
Results
Since the Hausman test confirmed the fixed-effects model, the Wald test confirmed the presence of heteroskedasticity, and the Wooldridge test confirmed first-order autocorrelation in the error terms for both groups of countries, and given that the number of cross-sections (N) is larger than the time periods (T), the PCSE estimator is used for estimation. The results for oil-rich developing countries indicate a negative relationship between the rule of law, corruption control, regulatory quality, and budget deficit fluctuations. In non-oil developing countries, a negative relationship between institutional quality indicators and budget deficit fluctuations was confirmed. A comparison of the results between the two groups shows that the impact of corruption control and regulatory quality on budget deficit fluctuations is stronger in oil-rich developing countries.
Conclusion
According to the findings, the effects of corruption control and regulatory quality on budget deficit fluctuations are stronger in oil-rich developing countries, while the effect of the rule of law is stronger in non-oil developing countries.
Public Sector Economics
Shahryar Zaroki; Mehdi Hasanpour Varkolaei; Ebadollah Aghaei Anarmarzi; Fatemeh Azhari
Abstract
Economic welfare, as a key indicator of development, plays a vital role in improving living standards and the economic sustainability of countries. One of the factors influencing economic welfare is the size and growth of the population. Therefore, understanding the impact of population growth ...
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Economic welfare, as a key indicator of development, plays a vital role in improving living standards and the economic sustainability of countries. One of the factors influencing economic welfare is the size and growth of the population. Therefore, understanding the impact of population growth on economic welfare is crucial for informing policy decisions. To this end, the present study aims to investigate the effect of population growth on economic welfare in Iran during the period of 1971 to 2023, using two autoregressive distributed lag (ARDL) models, symmetric and asymmetric (NARDL). The results of the first (symmetric) model show that population growth has a negative effect on economic welfare in both the short and long term. The results also indicate that per capita income, economic growth, and government size have a positive and significant effect on economic welfare. The inflation rate also has a negative and significant effect on welfare, while the unemployment rate has no significant effect. The results of the second (asymmetric) model also show that an increase in population growth (positive shocks) negatively impacts economic welfare, while a decrease in population growth (negative shocks) has no significant effect. The other results also indicate that per capita income, economic growth, and government size have a positive and significant effect on economic welfare. The inflation rate also has a negative and significant effect on welfare, but the unemployment rate does not have a significant effect on economic welfare. According to the findings of this study, adopting policies based on controlling and regulating the level of population growth, along with effective policies in managing inflation and strengthening production, can play an important role in increasing economic welfare and achieving sustainable development in the country.
Introduction
Economic welfare is an important indicator of development and quality of life, and achieving a desirable level of it is the goal of development policies. Researchers examine factors such as economic policies, institutional structures, technology, inflation, economic fluctuations, and population growth. Population growth can have a positive or negative impact on this indicator. In recent decades, the relationship between population growth and economic welfare has gained importance, particularly in developing countries like Iran. Population growth may increase the need for public services, education, and health, but it puts pressure on resources and infrastructure, which affects welfare. A gradual decrease in population facilitates sustainable development, but its decline leads to population aging and economic, social, health, and cultural problems. At the macro level, population decline increases welfare and retirement costs, reduces the labor force, and decreases productivity. Also, a decline in population growth leads to a decrease in savings and slows economic growth. As a result, population balance and understanding its long-term relationship with welfare is important for policymaking. In recent decades, Iran has faced sanctions, exchange rate fluctuations and inflation, reduced trade, increased inflationary expectations, a shortage of supply expenditures, and a decline in purchasing power, which has made the economy challenging. Changes in government revenue cause exchange rate and GDP fluctuations and financial shocks, affecting prices and inflation. Studies in developing countries show differences in the relationship between population growth and welfare; some show a negative relationship and some show complex relationships. Piketty suggests that if population growth and per capita production were independent, higher population growth would contribute to economic growth. However, if it affects per capita growth, a high rate of population growth can affect growth and inflation, and new methods of analysis have made these relationships possible. This article uses a composite index of economic welfare in Iran for the first time, which provides a more comprehensive analysis. The effect of the population growth rate on Iran's welfare in the period 1350-1402 (1971-2023) has been investigated using autoregressive methods, both long-term and short-term. The findings emphasize the importance of population and economic policies for sustainable development and can guide policymakers in developing long-term strategies to facilitate development and improve the quality of life.
Research Question(s)
Does population growth affect economic welfare in Iran?
Does population growth have a positive effect on economic welfare, or a negative effect?
Does population growth have an asymmetric effect on economic welfare?
Methods and Material
In this research, the Composite Index of Wellbeing (IEWB) is used to assess economic welfare, which considers the dimensions of effective consumption, wealth stock accumulation, income inequality, and economic insecurity, with the weight of each dimension varying based on observations. Its general form is as follows: IEWB=CF+WS+ID+ES. The welfare index has been calculated for the period 1350-1402 (Iranian calendar) using the aforementioned method. The aim of the study is to investigate the impact of population growth on welfare, using ARDL and NARDL models, which allow for the analysis of short-term and long-term relationships and the asymmetric effects of shocks. NARDL allows for the separation of positive and negative effects of variables; therefore, the impact of increasing and decreasing population growth rates on welfare is examined separately. The following specifies the unrestricted Autoregressive Distributed Lag (ARDL) model:
In the second model, based on the autoregressive distributed lag (ARDL) method with asymmetric lags (NARDL), it is specified in the following equation:
Results and Discussion
Before estimating the model, the stationarity of the variables was examined using the Augmented Dickey-Fuller and Phillips-Perron tests. The results indicate that only economic growth is stationary at the level; the other variables become stationary after first differencing. Accordingly, linear and nonlinear autoregressive models can be used. Diagnostic tests show that the hypotheses of no autocorrelation, normality, homoscedasticity, and homogeneity of variance are not rejected. The bounds test also confirms the existence of a long-run relationship between the variables with 90% confidence; therefore, the null hypothesis of no long-run relationship is rejected. In the autoregressive distributed lag model, the optimal lag was selected based on the Schwarz-Bayesian information criterion (minimum of 3). The estimation results indicate that population growth has a negative effect, and per capita income has a positive effect on welfare. Inflation has a negative effect, and economic growth has a positive effect, as does the size of government. The unemployment rate has no significant effect, and the sanctions variable has a negative effect, such that welfare has decreased during this period. The error correction coefficient is significant and indicates that approximately 64% of the welfare deviation is corrected in each period. The long-run results indicate that population growth with a negative coefficient has an inverse relationship with welfare, and per capita income with a positive coefficient improves welfare. Inflation with a negative coefficient has a negative effect on welfare, and economic growth with 0.27 has a positive effect, increasing the level of welfare. The size of government has a positive effect in the long run, and the unemployment rate has no significant impact.
Also, in the second model, the optimal lag was selected as 3 based on the Schwarz-Bayesian criterion in the minimum state. The results show that an increase in population growth has a negative impact on welfare; a decrease in growth has no significant effect, which indicates asymmetric behavior in its impact. Per capita income has a positive effect, inflation has a negative effect, and economic growth has a positive effect. The effect of government size is positive in the short term, but the unemployment rate has no significant effect. The post-JCPOA (Joint Comprehensive Plan of Action) impact is negative, and welfare has decreased by about 14 units in the period 1396-1402 (Iranian calendar). The error correction coefficient is significant and shows that 60% of the welfare deviation is adjusted each year. In the long run, increasing population growth reduces welfare. Population decline has no significant effect. Per capita income has a positive effect on welfare. Inflation has a negative long-term effect, economic growth has a positive effect, and government size also has a positive effect, but the unemployment rate has no significant effect.
Conclusion
Population growth is a significant factor in economic and social dynamics, influencing age structure, migration, inequality, the labor market, and production capacity. Malthus (1798) believed that rapid population growth would lead to reduced welfare and poverty in the long run because increased income for the poor would lead to population growth and decreased productivity. Recent research, such as Peterson (2017), has shown that population growth in low-income countries, especially with high fertility rates, has negative consequences, while decreased mortality has more positive effects. The results of this study, using linear and non-linear autoregressive models, indicate that the average economic welfare in Iran during 1350-1402 (1971-2023) is about 44.26 percent. Welfare had an upward trend in the 1350s (1970s) but fluctuated later, reaching 62.62 percent during the Fifth Development Plan and decreasing from 1399 to 1402 (2020-2023), coinciding with the post-JCPOA sanctions. The NARDL model shows that population growth negatively impacts welfare, but a decrease in population growth has a positive, though insignificant, effect. Without sufficient infrastructure, uncontrolled population growth puts pressure on resources and reduces welfare. Long-term inflation has a strong negative effect on welfare, while economic growth and per capita income improve the situation, according to the growth and Friedman's permanent income theories. Government size also has a positive effect, indicating the government's role in services and welfare. The unemployment rate does not have a significant effect, perhaps due to structural or support reasons. The results suggest that population policymaking in Iran should be done carefully and based on economic and social capabilities. Population growth can contribute to economic growth in some circumstances, but without the necessary infrastructure, it can negatively affect welfare. Policies should aim for an optimal growth rate. The experience of economically successful countries shows that combining population policies with economic policies such as subsidies and tax exemptions provides a balance between growth and welfare. Future research should focus on determining the optimal point of population growth and examining its complex relationship with welfare in the country's institutional structure. Also, studying the difference in the optimal rate in different regions can design effective regional policies and be an important tool for policymakers in areas such as family, education, and employment.
The Economics of Technology, Energy and Sustainable Development
Sanaz Shahbazi; Hassan Heidari; Mehdi Nejati
Abstract
Concerns about energy prices, environmental sustainability, and economic stability highlight the need to examine the effects of energy market liberalization, as fluctuations in oil and gas prices have profound impacts on economic and environmental variables. This study, based on a dynamic computable ...
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Concerns about energy prices, environmental sustainability, and economic stability highlight the need to examine the effects of energy market liberalization, as fluctuations in oil and gas prices have profound impacts on economic and environmental variables. This study, based on a dynamic computable general equilibrium model and GTAP-E database, investigates the impact of energy price liberalization on environmental variables and mineral products across three country groups—Iran, its major trading partners, and the rest of the world—under two scenarios: (1) a 5% gas price shock and (2) a 5% oil price shock, projecting up to the year 2050. The simulation results show that for Iran, the first scenario leads to a gradual and sustained reduction in carbon dioxide emissions, reflecting a negative relationship between CO₂ emissions and gas prices due to decreased fossil fuel consumption and a shift towards more efficient or alternative energy sources in mineral production. The second scenario results in a smaller but still significant reduction in carbon dioxide emissions. For Iran’s trading partners, the first scenario results in a long-term emission reduction owing to higher production costs and adoption of cleaner technologies, while the second scenario leads to faster reductions due to the mining sector’s dependency on oil and accelerated investments in energy-saving measures. For other regions, the first scenario shows an initial moderate reduction in carbon dioxide emissions followed by a temporary rebound, indicating delayed decarbonization; scenario two, however, leads to a sustained decline, underscoring the key role of oil in energy and mining sectors. The findings emphasize that energy price liberalization must be aligned with market realities and should promote improved consumption efficiency and innovation in clean technologies.
Introduction
Energy market liberalization, particularly through the removal of subsidies and the alignment of domestic energy prices with international levels, has been a subject of growing interest due to its potential implications for economic efficiency, fiscal sustainability, environmental outcomes, and energy security. Fluctuations in oil and gas prices significantly influence macroeconomic variables, industrial competitiveness, and greenhouse gas emissions, particularly in resource-dependent economies like Iran. This study adds to the existing literature by using a dynamic computable general equilibrium (DCGE) model based on the GTAP-E database, an extension of the standard GTAP framework that explicitly incorporates energy substitution, fossil fuel combustion, and CO₂ emissions (Burniaux and Truong, 2002) to analyze the long-term effects of energy price liberalization on CO₂ emissions in mineral production sectors.
While prior research has utilized GTAP-E in static or limited dynamic contexts, the application of a fully dynamic version with intertemporal adjustments, solved using GEMPACK algorithms and drawing on comprehensive regional and sectoral data from the GTAP database, represents a methodological advancement. This approach enables detailed projections up to 2050 and captures sector-specific responses in mineral industries, which are particularly energy-intensive and play a key role in Iran's economy and trade. The central research question is: How does energy price liberalization modeled as exogenous shocks to natural gas and oil prices affect CO₂ emissions in mineral production across Iran, its major trading partners, and the rest of the world?
Methods and Material
This study employs the Global Trade Analysis Project-Energy (GTAP-E) model, a multi-region, multi-sector, multi-agent computable general equilibrium (CGE) framework developed by Burniaux and Truong (2002). GTAP-E extends the standard GTAP model (Hertel, 1997) by explicitly incorporating energy substitution mechanisms and the linkage between energy consumption and greenhouse gas emissions, particularly CO₂ emissions from fossil fuel combustion. This allows for a detailed analysis of the environmental and economic impacts of energy price changes across sectors, regions, and agents. The multi-regional structure of GTAP-E provides significant advantages over single-region models by capturing inter-sectoral, inter-country, and inter-factor linkages on a global scale (Wu et al., 2019). Computable General Equilibrium (CGE) models have been widely applied in energy and environmental policy analysis since the 1980s, offering a consistent framework for evaluating the economic and environmental consequences of policy interventions (Rao et al., 2017; Chi et al., 2014). Their comprehensive treatment of resource allocation distortions caused by energy subsidies further justifies their use in this context (Manzoor et al., 2021).
To capture long-run dynamics and cumulative effects of policy reforms, this study employs a dynamic version of the GTAP-E model (DCGE). Unlike static CGE models, which are limited in their ability to account for growth effects, capital accumulation, and transitional paths, dynamic CGE models incorporate intertemporal adjustments, enabling realistic projections of medium- to long-term impacts where short-run and long-run effects may differ substantially (Zhang et al., 2020). The model is calibrated using the GTAP-E database and solved with GEMPACK software, allowing for the simulation of exogenous energy price shocks and their propagation through the global economy up to 2050.
Results and Discussion
Carbon intensity (CO₂ emissions per unit output) measures sectoral carbon efficiency. Table 4 reports changes under two 5% price shock scenarios—gas (Scenario 1) and oil (Scenario 2)—for Iran, trading partners, and other regions. The moderate price shock corresponds to historical fluctuations, consistent with prior studies (Eskandaripour et al., 2023; Lebrand et al., 2023).
In Iran, Scenario 1 reduced intensity markedly in oil (-26.22%), industry (-42.6%), minerals (-11.09%), and services (-13.27%) via cost-induced efficiency, but increased electricity (+46.9%) due to substitution to dirtier fuels (Barro et al., 2025). Gas intensity fell (-8.37%). Scenario 2 raised intensity in oil (+26.39%), gas (+4.69%), industry (+10.74%), and electricity (+16.73%) from fuel switching, while lowering it in agriculture (-16.12%), minerals (-8.93%), and services (-8.63%).
Trading partners exhibited heterogeneous responses: Scenario 1 increased gas (+0.52%) and coal (+0.23%) most; Scenario 2 amplified oil (+1.31%) and coal (+1.69%) rises, offset by non-energy sector declines. Other regions showed mostly reductions under Scenario 1 (except gas +0.65%, coal +0.29%), but energy sector increases under Scenario 2. Asymmetric patterns reflect fuel substitutability and sectoral vulnerabilities, implying uneven carbon pricing effects.
Table 5 shows fuel-specific CO2 emissions. Iran’s Scenario 1 raised oil/petroleum emissions but cut gas (-61.64%) and coal; Scenario 2 reversed oil trends. Trading partners shifted to coal/gas in Scenario 2; other regions reduced gas/petroleum more in Scenario 1 and oil in Scenario 2. Both scenarios trended downward overall.
Long-term mineral products CO2 emissions (Table 6, 2023–2050) declined steadily in Iran under Scenario 1 (~ -26.7 to -34 units) via efficiency incentives (Mosavi et al., 2017; Attílio et al., 2024), and less sharply under Scenario 2 (~ -9.5 to -12 units) due to lower oil substitutability (Ebaid et al., 2022). Trading partners had sharper Scenario 2 reductions (-0.95 by 2050); other regions showed sustained deepening under Scenario 2 (-0.87), consistent with oil-driven decarbonization and EKC dynamics (Kuznets, 1955; Zhou et al., 2021).
Gas shocks yield rapid gas-sector efficiency but risk dirty substitution in electricity; oil shocks promote broader long-term decarbonization. Policies should address substitution risks and facilitate technological transitions.
Conclusion
This study utilizes a dynamic computable general equilibrium (DCGE) model based on GTAP-E (version 10) data to simulate the effects of two energy price shocks—a 5% increase in natural gas prices and a 5% increase in oil prices—from 2023 to 2050. The results highlight distinct emission reduction pathways for Iran, its major trading partners, and the rest of the world, offering important insights for energy transition and climate mitigation policies.
In Iran, a natural gas price shock drives a gradual and sustained decline in greenhouse gas emissions, reflecting substitution toward cleaner energy sources and improved energy efficiency in mineral production. An oil price shock produces a milder but steady reduction, indicating lower substitutability in industrial sectors. These responses are consistent with the Environmental Kuznets Curve, where higher energy prices stimulate emission-reducing investments, with effects varying depending on sector-specific energy dependence and technological capacity. The reductions also stem from cleaner production technologies and a shift to low-carbon mineral products, consistent with Khan et al. (2022) and Antimiani et al. (2014).
Iran’s trading partners show a slow but steady emission decline under the gas price shock due to initial inelastic demand and subsequent technological adjustments. Oil price shocks lead to faster and sharper reductions, driven by greater oil reliance in their mineral sectors and stronger incentives for energy-saving innovations—patterns similar to those in developed industrial economies.
In other world regions, natural gas price increases result in an initial decline, temporary rebound, and eventual sustained reduction, reflecting structural rigidities and transition dynamics. Oil price shocks, however, cause more consistent and substantial declines, emphasizing oil’s pivotal role in global energy and industry.
Overall, energy price liberalization can effectively reduce greenhouse gas emissions, especially when supported by policies that promote technological innovation, energy efficiency, and cleaner alternatives in energy-intensive sectors. Region-specific policies are essential to balance environmental gains with economic impacts.
The Economics of Technology, Energy and Sustainable Development
Maryam Keyghobadi; Mohsen Kouhbor; Seyedeh Fatemeh Seyedmohsen
Abstract
The household sector, accounting for 28 percent of global energy consumption and 32 percent of greenhouse gas emissions, is a central focus of energy policy. While traditional policies have primarily emphasized technological interventions, evidence shows that reliance on such measures alone, without ...
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The household sector, accounting for 28 percent of global energy consumption and 32 percent of greenhouse gas emissions, is a central focus of energy policy. While traditional policies have primarily emphasized technological interventions, evidence shows that reliance on such measures alone, without attention to behavioral and social dimensions, cannot ensure sustainable effectiveness. This study aims to develop a localized framework for behavioral policymaking in Iran’s residential energy sector, employing a mixed-method approach in two stages. First, a meta-synthesis of global experiences was conducted to identify patterns of behavioral interventions. Second, a survey of 594 Tehran residents aged 18 and above was carried out, with data analyzed using multivariate regression techniques. The meta-synthesis revealed that information framing, feedback, and social norms were the most widely applied behavioral tools internationally. At the national level, however, lifestyle emerged as the strongest predictor of household energy consumption, while ethical-religious values and material culture also played a significant role. Integrating these two strands of evidence resulted in the development of a four-layered framework: (1) socio-cultural foundations; (2) behavioral operational interventions; (3) institutional and technological support and (4) policy capacity-building.This framework offers policymakers a practical roadmap for designing and implementing interventions that are both culturally resonant and technically sound, contributing to the sustainable management of residential energy consumption in Iran.
Introduction
The household sector is one of the largest consumers of energy worldwide, accounting for nearly 28% of global energy use and 32% of greenhouse gas emissions associated with energy consumption.
This situation underscores the urgency of designing effective policies to promote energy conservation and efficiency. Traditional approaches have largely relied on technological and infrastructural solutions such as smart meters, energy-efficient appliances, and insulation improvements. While these interventions remain essential, recent decades have highlighted the limitations of “hard” measures when implemented in isolation. A growing body of research in behavioral sciences has revealed that human decisions regarding energy use are shaped not only by structural or economic constraints but also by psychological, cultural, and social factors. Behavioral public policy, therefore, has emerged as a complementary approach, drawing on insights from behavioral economics, cognitive psychology, and social sciences to design interventions that are cost-effective, context-sensitive, and ethically grounded. However, the geographical spread and heterogeneity of behavioral interventions in the energy sector have made it difficult to achieve a coherent understanding of their applicability, especially in developing countries such as Iran.This study addresses this gap by developing a context-specific framework for behavioral policymaking in household energy consumption in Iran. By employing a dual-method approach—meta-synthesis of international behavioral policy experiences and a national survey among Iranian households—this research integrates global evidence with local insights. The goal is to develop a multi-layered framework that policymakers can use to design behavioral interventions tailored to Iran’s socio-cultural and institutional context.
Methods and Materials
A mixed-method design was employed to ensure comprehensive insights.
Phase I – Meta-Synthesis:
The first phase involved a meta-synthesis of 23 documented behavioral policy interventions implemented in different countries between 2000 and 2023. Behavioral policy interventions were identified using systematic searches of international databases and institutional reports, employing keywords such as “behavioral public policy” and “energy.” The interventions were analyzed along six dimensions:
Temporal and geographical scope
Target population
Operationalization strategies
Behavioral levers applied (e.g., nudges, feedback, framing)
Data collection methods
Tools of intervention (e.g., smart meters, gamification, mobile applications).
Phase II – National Survey:
The second phase employed a large-scale survey among Iranian households to capture context-specific drivers of energy consumption behavior. The survey targeted residents of Tehran aged 18 and above, using random sampling. A total of 594 valid responses were collected. The questionnaire measured awareness, attitudes, values, lifestyle, material culture, and demographic characteristics.
Validity was ensured through expert reviews and pilot testing, while reliability was tested using Cronbach’s alpha across pre-test and final samples. Data were analyzed using SPSS through descriptive statistics, correlation tests, and multiple regression analysis to identify key behavioral determinants.
Results and Discussion
Meta-Synthesis Findings
The international evidence indicated a growing prevalence of behavioral interventions, particularly in Europe (56) and Asia (35), with rapid acceleration since 2018. The most frequently employed levers included:
Information framing(14 instances),
Feedback mechanisms(11 instances),
Social norms and comparative feedback(11 instances).
Technological tools such as smart meters, IoT-enabled devices, and gamification-based applications were widely utilized to enhance feedback mechanisms. Interventions relying on framing showed that the way information is presented significantly influences consumer behavior, although their effects tended to diminish over time unless reinforced by reminders or gradual learning processes. Similarly, social norm-based interventions, such as providing households with comparative energy consumption reports, proved effective in shifting behaviors through peer influence.
Survey Findings in Iran
The survey results revealed several context-specific determinants of household energy consumption behavior:
Lifestylewas the strongest predictor of behavior (β = 0.234), highlighting the formative role of family and early socialization.
Moral and religious values(β = 0.224) were also significant, with many respondents perceiving energy saving as an ethical and even religious duty.
Material culture(β = 0.103), such as housing infrastructure and appliances, had a measurable impact.
Age(β = 0.135) was positively correlated, while income (β = –0.138) and gender (β = –0.112) showed negative correlations with energy-saving behaviors.
Notably, awareness (ρ = 0.064) had no significant relationship with actual behavior, indicating that education and information provision alone are insufficient to change practices. Furthermore, while international evidence emphasized cost-based feedback, Iranian respondents identified intrinsic values of energy saving—rather than cost concerns—as their primary motivation, a finding that reflects the distorting effects of low tariffs and subsidies.
Integration and Framework Development
By synthesizing both sets of findings, the study proposes a four-layered framework for behavioral policymaking in Iran’s household energy sector:
Cultural-Social Foundations:Redesigning communication strategies to emphasize energy saving as a moral and religious value; empowering families as behavioral units; and promoting community-based role models.
Operational Behavioral Interventions:Combining global tools such as comparative smart bills and mobile notifications with locally resonant framings (e.g., responsibility toward future generations).
Institutional and Technological Support:Accelerating smart meter deployment, creating interactive digital platforms, and designing incentive schemes based on behavioral improvement rather than absolute consumption.
Institutional Capacity-Building:Establishing behavioral insights teams, experimental policy labs, and legal frameworks to institutionalize behavioral policymaking.
Conclusion
This study demonstrated the necessity of integrating behavioral insights into energy policy in Iran. While international evidence highlights the efficacy of nudges such as framing, feedback, and social norm mechanisms, the national survey underscores the decisive role of lifestyle, moral-religious values, and family orientation in shaping Iranian household energy behavior.
The findings emphasize that awareness alone cannot drive behavioral change, and reliance on cost-based incentives is ineffective in contexts with heavily subsidized energy. Instead, interventions must align with cultural and moral values to trigger intrinsic motivations. By combining global experiences with localized insights, the proposed framework offers policymakers a practical roadmap for designing sustainable and context-sensitive behavioral interventions.
The contribution of this research lies in demonstrating that effective energy policymaking requires a multi-layered approach that bridges technological solutions with behavioral levers while embedding them in institutional and cultural contexts. Such a strategy not only enhances the effectiveness of energy conservation policies but also contributes to broader goals of sustainable development and climate change mitigation.
Financial Economics
Reza Asadi; Farzad Karimi; Saeid Aghasi
Abstract
In recent years, as the interdependence of different markets has increased, the level of financial risk of developing countries exporting industrial goods has increased. The main objective is to assess the extent to which industrial exports of these countries are affected by country financial risk ...
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In recent years, as the interdependence of different markets has increased, the level of financial risk of developing countries exporting industrial goods has increased. The main objective is to assess the extent to which industrial exports of these countries are affected by country financial risk and its components in comparison with traditional factors of bilateral trade such as economic size, real exchange rate, common border, and distance. In this paper, panel data for the period 2022 to 2002 are used within the framework of the Gravity Model and Pseudo-Poisson Maximum Likelihood (PPML) method. According to the findings of this study, the country financial risk conditions of developing countries have the greatest impact compared to other classic factors of bilateral trade. This study also showed that among the determinants of country financial risk, with the exception of external debt risk, reducing current account risk, service debt, exchange rate stability, and international liquidity risk leads to growth in industrial exports of developing countries. Therefore, an approach to assessing country financial risk and its effective management is crucial for developing countries exporting industrial goods. Thus, it is suggested that policies for managing these risks, including identifying them, assessing their impact on trade, prioritizing them, and developing measures to overcome them, should be on the agenda of export planners and policymakers in developing countries to minimize the negative impact on exports and prevent the negative impacts in the future.
Introduction
Currently, high correlation between different markets, increasing unilateralism and trade protectionism of developing countries have led to the spread of risk and uncertainty in these countries. One of the risks threatening industrial exports is country financial risk, which arises from fluctuations in exchange rates and government debt, affecting trade budgets and profitability. This category of risks represents an important hidden transaction cost and determines the flow of international trade in bilateral or multilateral industrial goods and therefore should be considered in any empirical model of international trade. The country financial risk considered in this study is a measure of a country's ability to meet its financial obligations at the international level. The country financial risk index is a combination of external debt risk, external service debt, current account, international liquidity and exchange rate stability. The main issue of the article is to identify the degree of influence of developing countries' industrial exports on country financial risk and its determining components in comparison with other factors affecting the exports of this group of countries.
Given that so far the discussion of the effect of country financial risk in the industrial export model has been very limited, and also the research conducted with an approach that has focused only on one of the country risk factors; therefore, the present study, in addition to examining the effect of country financial risk, also examines the importance of each of its determining components on the industrial exports of developing countries in comparison with other classic factors determining industrial exports. The result of this study can provide more effective and useful decision-making areas for developing countries that have always faced various types of deterrent risks in the course of international exchanges in the last four decades.
The present study can contribute to the discussion of decision-making in the field of industrial exports of developing countries from three perspectives: First, the factors affecting developing countries’ exports, especially from the perspective of country financial risk and at the industry sector level, are identified and a model for the development of industrial exports of these countries is presented. In fact, the industrial export model of developing countries is identified and explained by considering country financial risk along with other determinants of bilateral trade. Second, based on the latest available domestic and foreign studies that have emphasized traditional influential factors, such as economic factors, supply and demand factors, and distance on industrial export patterns of developing countries, the impact of country financial risk on industrial exports remains largely unknown. However, many researchers argue that country risk, such as financial risk, is a key factor that should be considered with regard to international trade policy. Third, the impact of developing countries’ financial risk in terms of each of its determinants is also considered. The results of these assessments will ultimately provide the basis for a more realistic analysis of the selection of important and influential drivers of industrial exports in developing countries.
Methods and Material
In the present study, based on the modified Gravity Model of Anderson and Van Wynkoop (2003) and also based on the aforementioned empirical studies such as Kai et al. (2022) and Jahanbakhsh Pour-Jabbari et al. (1402), the proposed Gravity Model is presented in terms of the financial risk index and separately for each of its constituent components as equations (2) to (7):
Model (2) assesses the impact of the country's financial risk index (FRR):
Model (3): for assessing the impact of the external debt risk index (fd):
Model (4): for assessing the impact of the external debt service risk index (fds):
Model (5): for assessing the impact of the current account risk index (ca):
Model (6): for assessing the impact of the international liquidity risk index (nil):
Model (7): for evaluating the impact of the exchange rate stability risk index (ers):
In models (2) to (7), t represents the year, i denotes the country of origin (exporter of industrial goods), and j denotes the country of destination, v_i and u_j with country fixed effect and δ_t is the period fixed effect and ε_ijt is the random error. Also, the variable xcdv is the value of industrial exports of developing countries. As mentioned, the country financial risk of this study is a measure of a country's ability to fulfill its financial obligations at the international level. The country financial risk index (FRR) variable is a composite index that evaluates five financial variables, namely the external debt risk index (FD), the external debt service risk index (FDS), the current account risk (CA), the international liquidity risk (NIL) and the exchange rate stability risk (ERS) and their associated risk points. The range of the indices varies between zero and 50; the closer the index is to zero, the higher the risk, and the closer it is to 50, the lower the risk. To ensure comparability between countries, the components are based on the accepted ratios between them. In general, a financial risk index of 0.0 to 24.5 percent indicates very high risk, 0.25 to 29.9 percent high risk, 0.30 to 34.9 percent medium risk, 0.35 to 39.9 percent low risk, and 0.40 percent or more very low risk. Information on the country financial risk index and its determinants was purchased from prsgroup.com. The raw data is monthly and is used in this study after averaging.
Results and Discussion
The results indicate that, in the medium term, unlike the long term, financial risks in developing countries are growing, which affects the development of industrial exports. Another point to be examined is that, at the same time as the country's financial risks increase, the growth of industrial exports has also become lower than the long-term industrial export growth rate. During the study period, the growth of industrial exports was 17.3 percent per year, significantly lower than the long-term growth rate of 67.9 percent. The distribution of industrial exports of developing countries in terms of country financial risk and its determinants in terms of the average period of 2002-2022 shows that many developing countries exporting industrial goods have low country financial risk during the period under study; hence, very little industrial exports of developing countries in an uncertain environment are exported to the global market in this respect.
The results of estimating the industrial export attraction model of developing countries in the form of six attraction models, taking into account the country financial risk index (FRR) and 5 determinants including the current account risk index (CA), debt service risk (FDS), external debt risk (FD), exchange rate stability risk (ERS), and international liquidity risk (NIL), show that the coefficient of the variable of the country financial risk index of developing countries in the industrial export attraction model is positive as expected and statistically significant at the 1 percent error level. The coefficients of the stated variables that show the elasticity of industrial exports of developing countries to the country financial risk of this group of countries are 2.588 units. Specifically, with a one percent increase in the country financial risk index of developing countries, there is a 2.588 percent increase in the growth of industrial exports of developing countries. The sign of the coefficient of the variable of the country financial risk index of export destinations in the industrial export attraction model is negative and statistically significant at the 1 percent error level. The coefficients of the variables that indicate the elasticity of developing countries' industrial exports to the country financial risk of developing countries' export destinations are -0.968. Specifically, with a one percent increase in the country financial risk index of export destinations (risk reduction), the growth of developing countries' industrial export demand decreases by 0.968. This empirical finding leads to the conclusion that reducing the country risk of export destinations is not only an important and important determinant of stimulating the demand for developing countries' industrial exports, but also leads to a decrease in the demand for developing countries' industrial exports. The results also show a positive and statistically significant effect of the five components of developing countries' country financial risk and export destinations on the industrial exports of these countries. Among the five components determining the country financial risk of developing countries, current account risk (ca), debt service (fds), exchange rate stability (ers) and international liquidity risk (nil) have a positive and significant effect on industrial exports of developing countries at the 1 percent error level. This is while the external debt risk component (fd) of developing countries does not have a significant relationship with industrial exports of this group of countries at a statistically acceptable level. Among the components affecting industrial exports, three components of current account risk (3.253), debt service risk (1.167) and exchange rate stability risk (1.111) have elasticity above one and international liquidity (0.417) has elasticity less than one in the industrial export model of developing countries. The results related to the impact of the country financial risk components of export destinations of developing countries show that the coefficients of all 5 components determining the country financial risk of export destinations are statistically significant at the 1 percent error level. Meanwhile, the coefficients of the current account risk components (-0.596), service debt (-0.642), external debt (-0.190), and international liquidity (-0.129) are negative, which indicates that with an increase in the coefficients of these components (risk reduction) of export destinations, the demand for industrial exports of developing countries decreases. In contrast, the exchange rate instability risk component (0.608) has a positive coefficient, and thus, with an increase in the exchange rate instability risk of export destinations (risk reduction) by one percent, the demand for industrial exports of developing countries increases by 0.608 percent.
Conclusion
This study focuses on examining the impact of country financial risk on industrial exports of developing countries and the role of each of its determinants. Based on the literature, trends, determinants, and the impact of each of the classical factors affecting bilateral trade have been examined along with the determinants of country risk.
The results of the descriptive analysis of trends show that many developing countries exporting industrial goods in the period under study have low country financial risk, which indicates that industrial exports of developing countries have been made to the world market in an environment of very little uncertainty in this regard. A large share of the low risk mentioned in developing countries is due to the low country current account risk, service debt risk, and exchange rate stability risk. Also, a high share of developing countries' exports is exported to countries that have very little uncertainty in the area of country financial risk.
It is noteworthy that from 2011 to 2022, the level of country financial risk in developing countries increased, contrary to the trend in industrial exports. This indicates an increase in country financial risk and uncertainty in the financial sector in this group of countries since 2011. The increase in this uncertainty in recent years is more evident in the areas of external debt, international liquidity, and exchange rate stability. This is while the risk of service debt and account risk has decreased. Therefore, the results of examining the trends of country financial risk in developing countries indicate that in recent years, the financial risks of this group of countries for the development of industrial exports to the world in the field of industrial goods have been growing. Another point of the study is that, at the same time as country financial risks have increased, the growth of industrial exports has slowed down. Econometric analysis confirms the role of country financial risk in the growth of industrial exports of developing countries. Similarly, the country financial risk conditions of developing countries and export destinations are introduced as one of the effective factors in the growth of industrial exports of developing countries. It is noteworthy that the country financial risk conditions of developing countries have the greatest impact on industrial exports compared to other classical factors of the Gravity Model such as economic size, distance and common border and have a demand elasticity of one. Among the five components determining the country financial risk of developing countries, reducing current account risk, service debt, exchange rate stability and international liquidity risk have a positive effect on the growth of industrial exports of developing countries. This is while increasing the country financial risk, current account, service debt and international liquidity risk of export destinations reduces the growth of industrial exports of developing countries, which confirms the results of the studies of Kai et al. (2022) on the impact of country financial risk. Of course, increasing the exchange rate stability risk of export destinations reduces the growth of industrial exports of developing countries. This is an important empirical finding in terms of the different roles of developing countries’ country financial risk and export destinations on the growth of developing countries’ bilateral industrial exports. Since financial risk has the fastest impact on the cash flows and income of developing countries’ industrial export firms, it seems that industrial manufacturing firms in these countries manage risk by expanding their export activities within the framework of regional cooperation in order to be less exposed to financial risk.
Policymakers seeking to reduce the consequences of financial risk as a tool for developing countries’ industrial exports should consider strengthening institutional quality to improve country risk management by international and regional organizations facilitating financial flows as a primary strategy for developing regional cooperation among developing countries; therefore, increasing institutional capabilities to manage the risk of developing countries’ export firms is essential as a key issue in regional cooperation.
Other innovative economic areas
Mahdi Basouli; Mansoureh Sadat Tabatabaei Soltanabad
Abstract
The tourism industry is known as one of the main drivers of development in many countries. However, seasonal fluctuations in tourism demand, as one of the major challenges of this industry, have significant impacts on the economy, society and environment. The aim of this research is to identify ...
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The tourism industry is known as one of the main drivers of development in many countries. However, seasonal fluctuations in tourism demand, as one of the major challenges of this industry, have significant impacts on the economy, society and environment. The aim of this research is to identify appropriate management solutions to improve the challenges of seasonal fluctuations in tourism demand in Yazd Province. The type of research is analytical-descriptive. Library resources and interviews were used to collect information. The technique used in this research is cognitive mapping. The statistical population is 75 tourism experts in Yazd Province, and the snowball sampling method was used. FCMapper and UCINET6 software were used to analyze the data, and fuzzy cognitive maps were drawn. The research findings identified 15 key management strategies to reduce the negative effects of seasonal fluctuations, including developing seasonal events, targeted advertising, financial incentives, improving service quality, diversifying tourism products, and promoting sustainable tourism. The analyses identified collaboration with government and local organizations, planning for religious tourism, and planning for domestic tourism as key factors with the greatest centrality and influence on other factors. The results of this research show that implementing the identified strategies can help reduce seasonal fluctuations, increase tourism demand in the off-season, and improve the tourism situation in Yazd Province.
Introduction
Tourism is a pivotal driver of economic growth, job creation, and cultural exchange globally and within Iran. Yazd Province, renowned for its unique historical, cultural, and architectural heritage registered as a UNESCO World Heritage site, holds significant potential as a prime tourist destination. However, like many seasonal destinations, Yazd faces the profound challenge of tourism demand fluctuations. These seasonal peaks and troughs lead to economic instability, underutilization or overburdening of infrastructure, volatile employment, and potential environmental strain during peak periods. Addressing this seasonality is crucial for achieving sustainable tourism development, maximizing year-round economic benefits, and ensuring the preservation of cultural assets. While seasonality is a known phenomenon, identifying and prioritizing context-specific, actionable management strategies to mitigate its negative impacts remains a critical research gap, particularly for heritage-rich regions like Yazd. This study aims to bridge this gap by systematically identifying and evaluating the most effective management strategies to alleviate seasonal tourism fluctuations in Yazd Province.
Literature Review
This research is grounded in several interlinked theoretical frameworks. Tourism Demand Theory explains how factors like climate, holidays, and pricing influence temporal visitation patterns. Strategic Tourism Management emphasizes the need for long-term, adaptive planning to overcome industry challenges like seasonality. Sustainable Tourism Development Theory provides the overarching goal, advocating for a balance between economic vitality, social equity, cultural integrity, and environmental protection—a balance disrupted by intense seasonality. Furthermore, Destination Competitiveness and Marketing Theories highlight the importance of creating a diversified, high-quality tourism product and implementing targeted promotional campaigns to attract visitors during off-peak seasons. Previous studies, both internationally and in Iran, have explored seasonality mitigation tools such as developing seasonal events, offering financial incentives, diversifying attractions, and leveraging digital marketing. This study builds upon this body of knowledge by applying an integrated analytical approach (Fuzzy Cognitive Mapping) to model the complex causal relationships between various management strategies within the specific context of Yazd.
Methodology
This applied research employs a descriptive-survey design and a mixed-methods approach. The study population consisted of 75 tourism experts (academics, government officials, and private sector professionals) in Yazd Province, selected via purposive and snowball sampling. The research process involved: 1) Conducting a comprehensive literature review and preliminary interviews to identify key management strategies for mitigating seasonality; 2) The development and validation of a matrix questionnaire where experts scored the causal influence between 15 finalized management strategies (e.g., developing seasonal festivals, targeted marketing, improving service quality, infrastructure development, promoting religious and domestic tourism, public-private collaboration); 3) The construction of individual and aggregated Fuzzy Cognitive Maps (FCMs) using FCMapper software to model the expert knowledge system, depicting each strategy as a concept node and their interrelationships as weighted causal links; 4) Analysis of the integrated FCM using UCINET6 software to calculate network centrality indices (influence, susceptibility, and total centrality) for each strategy, identifying the most pivotal levers within the system; 5) Simulation of different policy intervention scenarios to assess the potential systemic outcomes of focusing on different combinations of key strategies.
Results
The analysis of the integrated cognitive map (15 factors, 210 causal links) revealed the relative power and role of each management strategy. Based on centrality rankings, "Collaboration with Government and Local Organizations," "Planning for Religious Tourism," and "Planning for Domestic Tourism" emerged as the three most central and influential strategies. This indicates that synergistic institutional coordination and the strategic development of niche tourism segments (religious and domestic) are perceived by experts as having the greatest cascading positive effect on the entire system to counter seasonality.
Other significant strategies included diversifying tourism products, leveraging technology and digital marketing, and developing sustainable tourism infrastructure. Scenario simulations provided critical insights: isolated interventions on single factors yielded limited systemic improvement. For instance, focusing solely on institutional collaboration without parallel development in religious/domestic tourism planning resulted in only slow, moderate positive shifts across all factors. The findings underscore the necessity of an integrated, multi-pronged strategy that simultaneously activates the most central leverage points within the management ecosystem to achieve substantial and sustained reduction in seasonal volatility.
Conclusion and Future Research
This study successfully identified and prioritized a set of 15 management strategies to address tourism seasonality in Yazd Province. The core conclusion is that effective mitigation requires moving beyond isolated tactics towards a holistic, systems-based approach. The most critical action axis involves fostering strong collaboration between public and private entities to strategically develop and promote Yazd’s unique offerings—particularly to religious and domestic market segments—during off-peak seasons.Practical recommendations include: 1) Establishing a public-private tourism coordination council for Yazd to align efforts and resources. 2) Developing a detailed calendar of year-round cultural, religious, and seasonal events to attract visitors outside traditional peaks. 3) Creating and marketing tailored tourism packages for domestic and religious travelers targeting shoulder and low seasons. 4) Implementing coordinated digital marketing campaigns that highlight Yazd’s allure across all seasons. Future research could expand the geographical scope, incorporate tourist perception data, or employ longitudinal designs to measure the impact of implemented strategies. By adopting the identified integrated management solutions, stakeholders in Yazd can transform seasonal challenges into opportunities for resilient, sustainable, and year-round tourism development.
